Expert Recommendation for Answering Questions on Social Media
Source abstract
Abstract
In this paper, we propose a method for recommending experts to appropriately answer questions based on social activity analysis on social media. By analyzing various social activities performed on social media, the user’s interests are identified. Through the human relation analysis of the users of a particular interest field and by considering the response speed and answer quality of the user, we determine the influence of a user. An expert group is matched by analyzing the content of queries by a user and using a hierarchical structure of words. For a user question, the accuracy of an expert recommendation is enhanced by incorporating the question content and sublevel words based on the hierarchical structure of words. Various evaluations have demonstrated that the performance of the proposed method is superior to existing methods.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Expert finding and Q&A systems · Mobile Crowdsensing and Crowdsourcing · Recommender Systems and Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan 54538, Jeonbuk, Korea
Department of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju 28644, Chungbuk, Korea
Funding
National Research Foundation of Korea · Institute of Information & Communications Technology Planning & Evaluation(IITP)
References (33)
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